Table 1 HIV prevalence and the number of individuals included in PHIA survey
From: Use of unsupervised machine learning to characterise HIV predictors in sub-Saharan Africa
HIV prevalence | Number of individuals included in PHIA survey | |||
|---|---|---|---|---|
Country | Male | Female | Female | Male |
All countries | 6.4 | 10.2 | 155,622 | 146,733 |
Tanzania | 3.5 | 6.1 | 17,476 | 16,584 |
Rwanda | 2.1 | 3.6 | 16,015 | 14,700 |
Uganda | 4.8 | 7.9 | 15,822 | 14,131 |
Cameroon | 2.5 | 4.9 | 14,178 | 13,434 |
Zimbabwe | 11.6 | 15.2 | 13,240 | 11,794 |
Zambia | 9.6 | 14.4 | 10,994 | 10,286 |
Ethiopia | 2 | 4 | 10,058 | 10,112 |
Malawi | 8.8 | 12.3 | 10,242 | 9,587 |
Cote d'Ivoire | 1.7 | 3.7 | 9,274 | 9,653 |
Namibia | 9.8 | 15.7 | 9,705 | 9,091 |
Lesotho | 20.4 | 30.7 | 6,488 | 6,584 |
Swaziland | 21 | 32.5 | 6,393 | 5,482 |
Kenya | 3.1 | 6.5 | 15,737 | 15,295 |